Simulate & Predict
Get degradation context from early cycling data; accuracy not yet published.
Battery Digital Twin
Submit early-cycle data via API and get degradation context.
Key outcomes
Degradation-aware
decision output
What goes in
Inputs this feature expects
- Cycling data exported from battery tests
- Cell metadata and chemistry context when available
- Optional scenario assumptions for downstream planning
What comes out
Outputs your team can act on
- Projected capacity-retention trajectory
- A faster signal for go, kill, or reformulate decisions
Workflow
How teams use Battery Digital Twin
01
Load early-cycle data
Bring in the first portion of a test instead of waiting for the full campaign to finish.
02
Fit the digital twin
Lattice Graph estimates long-horizon behavior from the observed cycling signature.
03
Act while the test is still running
Flag weak-looking cells for review, so the team can decide early where to put lab capacity.
Best fit
Where this feature fits best
- Battery teams trying to shorten qualification loops
- Stopping low-value cycling campaigns early
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